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research-article

Multiple Model Adaptive Control of a Hybrid Solid Oxide Fuel Cell Gas Turbine Power Plant Simulator

[+] Author and Article Information
Alex Tsai

United States Coast Guard Academy, New London CT, USA
Alex.Tsai@uscga.edu

Paolo Pezzini

Ames Laboratory, Iowa State University IA, USA
ppezzini@ameslab.gov

David Tucker

US Department of Energy, National Energy Technology Laboratory, Morgantown WV, USA
david.tucker@netl.doe.gov

Dr. Kenneth Mark Bryden

Ames Laboratory, Iowa State University IA, USA
kmbryden@iastate.edu

1Corresponding author.

ASME doi:10.1115/1.4042381 History: Received May 30, 2018; Revised December 19, 2018

Abstract

A Multiple Model Adaptive Control (MMAC) methodology is used to control the critical parameters of a Solid Oxide Fuel Cell Gas Turbine (SOFC-GT) cyberphysical simulator, capable of characterizing 300kW hybrid plants. The SOFC system is comprised of a hardware Balance of Plant (BoP) component, and a high fidelity FC model implemented in software. This study utilizes empirically derived Transfer Functions (TF) of the BoP facility to derive the multi model adaptive controller (MMAC) gains for the BoP system, based on an estimation algorithm which identifies current operating points. The MMAC technique is useful for systems having a wide operating envelope with nonlinear dynamics. The practical implementation of the adaptive methodology is presented through simulation in the MATLAB/SIMULINK environment.

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